Search (53 results, page 1 of 3)

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Abstract

A new collaborative approach in information organization and sharing has recently arisen, known as collaborative tagging or social indexing. A key element of collaborative tagging is the concept of collective intelligence (CI), which is a shared intelligence among all participants. This research investigates the phenomenon of social tagging in the context of CI with the aim to serve as a stepping-stone towards the mining of truly valuable social tags for web resources. This study focuses on assessing and evaluating the degree of CI embedded in social tagging over time in terms of two-parameter values, number of participants, and top frequency ranking window. Five different metrics were adopted and utilized for assessing the similarity between ranking lists: overlapList, overlapRank, Footrule, Fagin's measure, and the Inverse Rank measure. The result of this study demonstrates that a substantial degree of CI is most likely to be achieved when somewhere between the first 200 and 400 people have participated in tagging, and that a target degree of CI can be projected by controlling the two factors along with the selection of a similarity metric. The study also tests some experimental conditions for detecting social tags with high CI degree. The results of this study can be applicable to the study of filtering social tags based on CI; filtered social tags may be utilized for the metadata creation of tagged resources and possibly for the retrieval of tagged resources.

Date

25.12.2012 15:22:37

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Abstract

This paper presents a methodological discussion of a study of tagging quality in subject indexing. The data analysis in the study was divided into 3 phases: analysis of indexing consistency, analysis of tagging effectiveness, and analysis of the semantic values of tags. To analyze indexing consistency, this study employed the vector space model-based indexing consistency measures. An analysis of tagging effectiveness with tagging exhaustivity and tag specificity was conducted to ameliorate the drawbacks of consistency analysis based on only the quantitative measures of vocabulary matching. To further investigate the semantic values of tags at various levels of specificity, a latent semantic analysis (LSA) was conducted. To test statistical significance for the relation between tag specificity and semantic quality, correlation analysis was conducted. This research demonstrates the potential of tags for web document indexing with a complete assessment of tagging quality and provides a basis for further study of the strengths and limitations of tagging.

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Abstract

The subject of this article is folksonomies on the Internet. One of the largest folksonomies on the Internet in terms of number of users and tagged websites is the computer program del.icio.us, where more than 100,000 people have tagged the websites that they and others find using their own keywords. How this is done in practice and the patterns to be found are the focus of this article. The empirical basis is the collection of 76,601 different keywords with a total frequency of 178,215 from 500 randomly chosen taggers on del.icio.us at the end of 2005. The keywords collected were then analyzed quantitatively statistically by uncovering their frequency and percentage distribution and through a statistical correspondence analysis in order to uncover possible patterns in the users' tags. Subsequently, a qualitative textual analysis of the tags was made in order to find out by analysis which tagging strategies are represented in the data material. This led to four conclusions. 1) the distribution of keywords follows classic power law; 2) distinct tagging communities are identifiable; 3) the most frequently used tags are situated on a general-specific axis; and 4) nine distinct tagging strategies are observed. These four conclusions are put into perspective collectively in respect of a number of more general and theoretical considerations concerning folksonomies and the classification systems of the future.

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Abstract

Colored Tags (abbr.Tag) as a unique type of social tags is used on e-commerce websites (e.g., Taobao) to summarize the high-frequency keywords extracted from users' online reviews about products they bought before. Tag is represented inked red or green according to users' personal experiences and judgments about purchased items: red for positive comments, green for negative ones. The valence of users' emotion induced by red or green is controversial. This study firstly discovers that colored tags inked in red incite users' positive emotion (evaluations) and colored tags inked in green incite negative emotion (evaluations) using an ERP experiment, which is manifested in ERP components (e.g., N170, N2c, and LPC). There are two main features of Tag: the text of Tag (abbr. Text) and the color of Tag (abbr.Color). Our study then proves that Color (red or green) is the dominant factor in users' decision behavior compared with Text under the high cognitive load condition, while users' decision behavior is influenced by Text (positive tags or negative tags) predominately rather than by Color under the low cognitive load condition with the help of Eye tracking instrument. Those findings can help to design colored tags for recommendation systems on e-commerce websites and other online platforms.

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Abstract

This paper examines collections of citations that individual users contribute to social tagging systems such as Delicious and LibraryThing. I characterize these personal collections, furnished with various forms of metadata and arranged for Web display, as a means of communication, where a particular sensibility molds guiding principles for resource selection, description, and categorization. Using several analytic frameworks from museum studies, I present three brief case studies that interrogate both the substance and the means of expression achieved in such collections, which I term "expressive bibliographies." In considering these case studies, I explore how an explicit rhetorical perspective might inform purposeful design of expressive bibliography.

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Abstract

This paper examines the context of online indexing from the viewpoint of three different groups: users, authors, and professional indexers. User tags, author keywords, and descriptors were collected from academic journal articles, which were both indexed in PubMed and tagged on CiteULike, and analysed. Descriptive statistics, informetric measures, and thesaural term comparison shows that there are important differences in the use of keywords among the three groups in addition to similarities, which can be used to enhance support for search and browse. While tags and author keywords were found that matched descriptors exactly, other terms which did not match but provided important expansion to the indexing lexicon were found. These additional terms could be used to enhance support for searching and browsing in article databases as well as to provide invaluable data for entry vocabulary and emergent terminology for regular updates to indexing systems. Additionally, the study suggests that tags support organisation by association to task, projects, and subject while making important connections to traditional systems which classify into subject categories.

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Date

21. 6.2009 12:22:44

Theme

Computer Based Training

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Abstract

Nach dem zu Beginn der Ära des World Wide Web von Hand gepflegte Linklisten und -Verzeichnisse und an Freunde und Kollegen per E-Mail verschickte Links genügten, um die Informationen zu finden, nach denen man suchte, waren schon bald Volltextsuchmaschinen und halbautomatisch betriebene Kataloge notwendig, um den mehr und mehr anschwellenden Informationsfluten des Web Herr zu werden. Heute bereits sind diese Dämme gebrochen und viele Millionen Websites halten Billionen an Einzelseiten mit Informationen vor, von Datenbanken und anderweitig versteckten Informationen ganz zu schweigen. Mit Volltextsuchmaschinen erreicht man bei dieser Masse keine befriedigenden Ergebnisse mehr. Entweder man erzeugt lange Suchterme mit vielen Ausschließungen und ebenso vielen nicht-exklusiven ODER-Verknüpfungen um verschiedene Schreibweisen für den gleichen Term abzudecken oder man wählt von vornherein die Daten-Quelle, an die man seine Fragen stellt, genau aus. Doch oft bleiben nur klassische Web-Suchmaschinen übrig, zumal wenn der Fragende kein Informationsspezialist mit Kenntnissen von Spezialdatenbanken ist, sondern, von dieser Warte aus gesehenen, ein Laie. Und nicht nur im Web selbst, auch in unternehmensinternen Intranets steht man vor diesem Problem. Tausende von indizierten Dokumente mögen ein Eckdatum sein, nach dem sich der Erfolg der Einführung eines Intranets bemessen lässt, aber eine Aussage über die Nützlichkeit ist damit nicht getroffen. Und die bleibt meist hinter den Erwartungen zurück, vor allem bei denen Mitarbeitern, die tatsächlich mit dem Intranet arbeiten müssen. Entscheidend ist für die Informationsauffindung in Inter- und Intranet eine einfach zu nutzende und leicht anpassbare Möglichkeit, neue interessante Inhalte zu entdecken. Mit Tags steht eine mögliche Lösung bereit.

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Abstract

With the increasing popularity of social tagging systems, the potential for using social tags as a source of metadata is being explored. Social tagging systems can simplify the involvement of a large number of users and improve the metadata-generation process. Current research is exploring social tagging systems as a mechanism to allow nonprofessional catalogers to participate in metadata generation. Because social tags are not from controlled vocabularies, there are issues that have to be addressed in finding quality terms to represent the content of a resource. This research explores ways to obtain a set of tags representing the resource from the tags provided by users. Two metrics are introduced. Annotation Dominance (AD) is a measure of the extent to which a tag term is agreed to by users. Cross Resources Annotation Discrimination (CRAD) is a measure of a tag's potential to classify a collection. It is designed to remove tags that are used too broadly or narrowly. Using the proposed measurements, the research selects important tags (meta-terms) and removes meaningless ones (tag noise) from the tags provided by users. To evaluate the proposed approach to find classificatory metadata candidates, we rely on expert users' relevance judgments comparing suggested tag terms and expert metadata terms. The results suggest that processing of user tags using the two measurements successfully identifies the terms that represent the topic categories of web resource content. The suggested tag terms can be further examined in various usages as semantic metadata for the resources.

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Abstract

A number of such utilities are presented here, together with an emergent new class of tools that caters more to the academic communities and that stores not only user-supplied tags, but also structured citation metadata terms wherever it is possible to glean this information from service providers. This provision of rich, structured metadata means that the user is provided with an accurate third-party identification of a document, which could be used to retrieve that document, but is also free to search on user-supplied terms so that documents of interest (or rather, references to documents) can be made discoverable and aggregated with other similar descriptions either recorded by the user or by other users. Matt Biddulph in an XML.com article last year, in which he reviews one of the better known social bookmarking tools, del.icio.us, declares that the "del.icio.us-space has three major axes: users, tags, and URLs". We fully support that assessment but choose to present this deconstruction in a reverse order. This paper thus first recaps a brief history of bookmarks, then discusses the current interest in tagging, moves on to look at certain social issues, and finally considers some of the feature sets offered by the new bookmarking tools. A general review of a number of common social bookmarking tools is presented in the annex. A companion paper describes a case study in more detail: the tool that Nature Publishing Group has made available to the scientific community as an experimental entrée into this field - Connotea; our reasons for endeavouring to provide such a utility; and experiences gained and lessons learned.

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Pages

S.15-22

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Pages

S.14-22

Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

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Date

1. 8.2010 12:35:22

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Date

10. 9.2000 17:38:22

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Date

10. 9.2000 17:38:22

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Source

¬Die Kraft der digitalen Unordnung: 32. Arbeits- und Fortbildungstagung der ASpB e. V., Sektion 5 im Deutschen Bibliotheksverband, 22.-25. September 2009 in der Universität Karlsruhe. Hrsg: Jadwiga Warmbrunn u.a

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Content

Vortrag anlässlich des Workshops: "Extending the multilingual capacity of The European Library in the EDL project Stockholm, Swedish National Library, 22-23 November 2007".

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Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

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Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

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Date

21. 4.2016 11:23:22